

from typing import Any

import numpy as np






def        snake_case__		(    lowerCamelCase_		):
							return np.array_equal(lowerCamelCase_     ,				matrix.conjugate().T		)






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							A      :					Union[str, Any]      		=					v.conjugate().T
							A      :					Any      		=					v_star.dot(lowerCamelCase_		)
							assert isinstance(lowerCamelCase_     ,				np.ndarray		)
							return (v_star_dot.dot(lowerCamelCase_		)) / (v_star.dot(lowerCamelCase_		))






def        snake_case__		(    ):
							A      :					Dict      		=					np.array([[2, 2 + 1J, 4], [2 - 1J, 3, 1J], [4, -1J, 1]]		)
							A      :					Any      		=					np.array([[1], [2], [3]]		)
							assert is_hermitian(lowerCamelCase_		), F'{a} is not hermitian.'
							print(rayleigh_quotient(lowerCamelCase_     ,				lowerCamelCase_		)		)

							A      :					Any      		=					np.array([[1, 2, 4], [2, 3, -1], [4, -1, 1]]		)
							assert is_hermitian(lowerCamelCase_		), F'{a} is not hermitian.'
							assert rayleigh_quotient(lowerCamelCase_     ,				lowerCamelCase_		) == float(3		)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		tests()









import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
		import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin







@require_torch
class 					__lowercase  (						unittest.TestCase		,       _SCREAMING_SNAKE_CASE				):





							"""simple docstring"""

							def       snake_case			(					self						)		->       Optional[Any]:
														A      :					Optional[Any]      		=					load_tool('''text-to-speech'''						)
														self.tool.setup()




							def       snake_case			(					self						)		->       Union[str, Any]:
														# SpeechT5 isn't deterministic
														torch.manual_seed(0						)
														A      :					Optional[Any]      		=					self.tool('''hey'''						)
														A      :					List[str]      		=					result.to_raw()
														self.assertTrue(
														    torch.allclose(
														        resulting_tensor[:3]    ,						torch.tensor([-0.0_0_0_5_9_6_6_6_6_8_8_3_2_1_1_5_8_2_9, -0.0_0_0_3_6_5_7_6_4_0_1_9_0_7_9_5_0_6_4, -0.0_0_0_1_3_4_3_9_5_0_2_7_9_9_8_8_3_4_8_5]						)    ,						)						)






							def       snake_case			(					self						)		->       Optional[Any]:
														# SpeechT5 isn't deterministic
														torch.manual_seed(0						)
														A      :					int      		=					self.tool('''hey'''						)
														A      :					Any      		=					result.to_raw()
														self.assertTrue(
														    torch.allclose(
														        resulting_tensor[:3]    ,						torch.tensor([-0.0_0_0_5_9_6_6_6_6_8_8_3_2_1_1_5_8_2_9, -0.0_0_0_3_6_5_7_6_4_0_1_9_0_7_9_5_0_6_4, -0.0_0_0_1_3_4_3_9_5_0_2_7_9_9_8_8_3_4_8_5]						)    ,						)						)






